{"id":"https://openalex.org/W3214430180","doi":"https://doi.org/10.1145/3531146.3533073","title":"Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash","display_name":"Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W3214430180","doi":"https://doi.org/10.1145/3531146.3533073","mag":"3214430180"},"language":"en","primary_location":{"id":"doi:10.1145/3531146.3533073","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533073","pdf_url":null,"source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3531146.3533073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058576517","display_name":"Lukas Struppek","orcid":null},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Lukas Struppek","raw_affiliation_strings":["Department of Computer Science, Technical University of Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016622690","display_name":"Dominik Hintersdorf","orcid":"https://orcid.org/0000-0003-4976-6894"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Hintersdorf","raw_affiliation_strings":["Department of Computer Science, Technical University of Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064701353","display_name":"Daniel Neider","orcid":"https://orcid.org/0000-0001-9276-6342"},"institutions":[{"id":"https://openalex.org/I4210121786","display_name":"Max Planck Institute for Software Systems","ror":"https://ror.org/02pe2kf23","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210121786"]},{"id":"https://openalex.org/I129877168","display_name":"Carl von Ossietzky Universit\u00e4t Oldenburg","ror":"https://ror.org/033n9gh91","country_code":"DE","type":"education","lineage":["https://openalex.org/I129877168"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Neider","raw_affiliation_strings":["Max Planck Institute for Software Systems, Germany and Safety and Explainability of Learning Systems, Carl von Ossietzky University of Oldenburg, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Software Systems, Germany and Safety and Explainability of Learning Systems, Carl von Ossietzky University of Oldenburg, Germany","institution_ids":["https://openalex.org/I129877168","https://openalex.org/I4210121786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037636074","display_name":"Kristian Kersting","orcid":"https://orcid.org/0000-0002-2873-9152"},"institutions":[{"id":"https://openalex.org/I4392021234","display_name":"Hessian Center for Artificial Intelligence","ror":"https://ror.org/014ybqb54","country_code":null,"type":"facility","lineage":["https://openalex.org/I31512782","https://openalex.org/I4392021234"]},{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kristian Kersting","raw_affiliation_strings":["Department of Computer Science and Centre for Cognitive Science, Technical University of Darmstadt, Germany and Hessian Center for Artificial Intelligence, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Centre for Cognitive Science, Technical University of Darmstadt, Germany and Hessian Center for Artificial Intelligence, Germany","institution_ids":["https://openalex.org/I31512782","https://openalex.org/I4392021234"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058576517"],"corresponding_institution_ids":["https://openalex.org/I31512782"],"apc_list":null,"apc_paid":null,"fwci":7.756,"has_fulltext":false,"cited_by_count":132,"citation_normalized_percentile":{"value":0.97948609,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"58","last_page":"69"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7788668870925903},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7652910947799683},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5346544981002808},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.4987311363220215},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4631615877151489},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.46053174138069153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44600996375083923},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4133444130420685},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11408570408821106},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10063272714614868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7788668870925903},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7652910947799683},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5346544981002808},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.4987311363220215},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4631615877151489},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.46053174138069153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44600996375083923},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4133444130420685},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11408570408821106},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10063272714614868},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3531146.3533073","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533073","pdf_url":null,"source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.06628","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.06628","pdf_url":"https://arxiv.org/pdf/2111.06628","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3531146.3533073","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533073","pdf_url":null,"source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1956333070","https://openalex.org/W2099471712","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2133665775","https://openalex.org/W2138621090","https://openalex.org/W2145023731","https://openalex.org/W2147717514","https://openalex.org/W2464915613","https://openalex.org/W2618604876","https://openalex.org/W2734963828","https://openalex.org/W2810966399","https://openalex.org/W2904169782","https://openalex.org/W2944779197","https://openalex.org/W2947272707","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2963207607","https://openalex.org/W2963857521","https://openalex.org/W2964121744","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2970971581","https://openalex.org/W2982083293","https://openalex.org/W3034600949","https://openalex.org/W3035574324","https://openalex.org/W3102700005","https://openalex.org/W3103557498","https://openalex.org/W3104876213","https://openalex.org/W3108980562","https://openalex.org/W3155075829","https://openalex.org/W3174316494","https://openalex.org/W3175311435","https://openalex.org/W3175328093","https://openalex.org/W3211902004","https://openalex.org/W4386313147","https://openalex.org/W6785841629"],"related_works":["https://openalex.org/W1983811306","https://openalex.org/W2365093105","https://openalex.org/W2997512100","https://openalex.org/W2331043530","https://openalex.org/W3048799479","https://openalex.org/W2731899572","https://openalex.org/W2393933887","https://openalex.org/W3215138031","https://openalex.org/W2779961139","https://openalex.org/W3009238340"],"abstract_inverted_index":{"Apple":[0],"recently":[1],"revealed":[2],"its":[3,24,150],"deep":[4,52,63,146],"perceptual":[5,53,64,147],"hashing":[6,54,65,148],"system":[7],"NeuralHash":[8],"to":[9,23,106,115],"detect":[10],"child":[11],"sexual":[12],"abuse":[13],"material":[14,114],"(CSAM)":[15],"on":[16,56,136,143],"user":[17,35,137],"devices":[18],"before":[19],"files":[20],"are":[21],"uploaded":[22],"iCloud":[25],"service.":[26],"Public":[27],"criticism":[28],"quickly":[29],"arose":[30],"regarding":[31],"the":[32,38,46,74,108,124,133],"protection":[33],"of":[34,51],"privacy":[36,168],"and":[37,161],"system\u2019s":[39],"reliability.":[40],"In":[41,139],"this":[42],"paper,":[43],"we":[44,59],"present":[45],"first":[47],"comprehensive":[48],"empirical":[49],"analysis":[50],"based":[55,142],"NeuralHash.":[57],"Specifically,":[58],"show":[60],"that":[61],"current":[62,151],"may":[66],"not":[67,155,163],"be":[68,130,164],"robust.":[69],"An":[70],"adversary":[71],"can":[72,128],"manipulate":[73],"hash":[75,98,125],"values":[76],"by":[77,85,90],"applying":[78],"slight":[79],"changes":[80],"in":[81,149],"images,":[82],"either":[83],"induced":[84],"gradient-based":[86],"approaches":[87],"or":[88,96],"simply":[89],"performing":[91],"standard":[92],"image":[93],"transformations,":[94],"forcing":[95],"preventing":[97],"collisions.":[99],"Such":[100],"attacks":[101],"permit":[102],"malicious":[103],"actors":[104],"easily":[105],"exploit":[107],"detection":[109],"system:":[110],"from":[111,166],"hiding":[112],"abusive":[113],"framing":[116],"innocent":[117],"users,":[118],"everything":[119],"is":[120,153],"possible.":[121],"Moreover,":[122],"using":[123],"values,":[126],"inferences":[127],"still":[129],"made":[131],"about":[132],"data":[134],"stored":[135],"devices.":[138],"our":[140,144],"view,":[141],"results,":[145],"form":[152],"generally":[154],"ready":[156],"for":[157],"robust":[158],"client-side":[159],"scanning":[160],"should":[162],"used":[165],"a":[167],"perspective.1":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":107},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}